一种基于设备健康数据智慧发电运行控制方法以及系统

By acquiring and processing the operating information of generator sets and power grids, dynamically adjusting the discrimination criteria and correcting the lubricating oil film model, the problem of misjudging early wear signals has been solved, enabling accurate identification and preventive intervention of early wear, and improving the accuracy of equipment health assessment and power grid stability.

CN122001095BActive Publication Date: 2026-07-17内蒙古蒙东能源有限公司

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
内蒙古蒙东能源有限公司
Filing Date
2026-02-06
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing power generation operation control systems are prone to misinterpreting early wear signals of generator sets as adaptive responses to normal grid fluctuations. This leads to inaccurate equipment health assessments, failure to provide timely preventative intervention, impacting power generation efficiency, and accumulating the risk of unplanned outages.

Method used

By acquiring the operating information of the generator set and the external power grid, performing preprocessing and correlation analysis, dynamically adjusting the judgment criteria, modifying the physical transmission model in combination with the dynamic characteristics of the lubricating oil film, conducting multi-dimensional matching and feature analysis, generating equipment health assessment reports and formulating operation intervention strategies.

Benefits of technology

It enables accurate identification and preventative intervention of early wear signals, improves the accuracy of equipment health assessment, reduces the risk of unplanned downtime, and ensures power generation efficiency and grid stability.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明涉及发电运行技术领域,公开了一种基于设备健康数据智慧发电运行控制方法及系统,通过获取发电机组的内部运行信息和外部电网运行信息,并进行预处理,能够全面掌握机组和电网的实时状况。在此基础上,识别发电机组的当前运行状态和外部电网的波动状态,为后续的分析提供了重要的情境信息。通过该方法,有效克服了现有系统在复杂工况下对早期磨损信号识别的局限性,避免了将潜在隐患误判为正常响应,从而提高了设备健康评估的准确性,降低了非计划停机风险,保障了发电效率和电网的稳定性。
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